The Performance of the Investment Return Prediction Models: Theory and Evidence
Abstract
The market structure has been adjusted in order to be as simple as possible in sense of its economic components. The aim of the investment return prediction is constructing as good models of the market movement as possible. As for as the stock market is concerned, the price rise of some stocks indicate the good results of the management of that company, while the price fall shows the inadequate management. Prompt and accurate information of the market movement enable the managers to take some measures which lead to optimal investment decision. The Autoregressive Moving Average (ARIMA) model is one of the most frequently linear models of the time series used for the investment return prediction. The prediction researches in the last years from the areas of Artificial Neural Networks (ANNs) indicate that ANNs with a combination of other prediction models give better prediction results. This research aim is to introduce a hybrid model ARIMA fuzzy-neural network for the prediction of the s...tock market index BELEX15 values. The research results indicate that the linear model ARIMA and fuzzy ANNs exhibit more superior investment return prediction performances.
Keywords:
Return / Prediction / Investment / ARIMA / ANNSource:
2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (Sisy), 2014, 221-225Publisher:
- IEEE, NEW YORK
Collections
Institution/Community
Fakultet zaštite životne sredineTY - CONF AU - Ralević, Nebojša AU - Glisović, Natasa S. AU - Đaković, Vladimir AU - Anđelić, Goran PY - 2014 UR - https://redun.educons.edu.rs/handle/123456789/227 AB - The market structure has been adjusted in order to be as simple as possible in sense of its economic components. The aim of the investment return prediction is constructing as good models of the market movement as possible. As for as the stock market is concerned, the price rise of some stocks indicate the good results of the management of that company, while the price fall shows the inadequate management. Prompt and accurate information of the market movement enable the managers to take some measures which lead to optimal investment decision. The Autoregressive Moving Average (ARIMA) model is one of the most frequently linear models of the time series used for the investment return prediction. The prediction researches in the last years from the areas of Artificial Neural Networks (ANNs) indicate that ANNs with a combination of other prediction models give better prediction results. This research aim is to introduce a hybrid model ARIMA fuzzy-neural network for the prediction of the stock market index BELEX15 values. The research results indicate that the linear model ARIMA and fuzzy ANNs exhibit more superior investment return prediction performances. PB - IEEE, NEW YORK C3 - 2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (Sisy) T1 - The Performance of the Investment Return Prediction Models: Theory and Evidence EP - 225 SP - 221 UR - conv_848 ER -
@conference{ author = "Ralević, Nebojša and Glisović, Natasa S. and Đaković, Vladimir and Anđelić, Goran", year = "2014", abstract = "The market structure has been adjusted in order to be as simple as possible in sense of its economic components. The aim of the investment return prediction is constructing as good models of the market movement as possible. As for as the stock market is concerned, the price rise of some stocks indicate the good results of the management of that company, while the price fall shows the inadequate management. Prompt and accurate information of the market movement enable the managers to take some measures which lead to optimal investment decision. The Autoregressive Moving Average (ARIMA) model is one of the most frequently linear models of the time series used for the investment return prediction. The prediction researches in the last years from the areas of Artificial Neural Networks (ANNs) indicate that ANNs with a combination of other prediction models give better prediction results. This research aim is to introduce a hybrid model ARIMA fuzzy-neural network for the prediction of the stock market index BELEX15 values. The research results indicate that the linear model ARIMA and fuzzy ANNs exhibit more superior investment return prediction performances.", publisher = "IEEE, NEW YORK", journal = "2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (Sisy)", title = "The Performance of the Investment Return Prediction Models: Theory and Evidence", pages = "225-221", url = "conv_848" }
Ralević, N., Glisović, N. S., Đaković, V.,& Anđelić, G.. (2014). The Performance of the Investment Return Prediction Models: Theory and Evidence. in 2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (Sisy) IEEE, NEW YORK., 221-225. conv_848
Ralević N, Glisović NS, Đaković V, Anđelić G. The Performance of the Investment Return Prediction Models: Theory and Evidence. in 2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (Sisy). 2014;:221-225. conv_848 .
Ralević, Nebojša, Glisović, Natasa S., Đaković, Vladimir, Anđelić, Goran, "The Performance of the Investment Return Prediction Models: Theory and Evidence" in 2014 IEEE 12th International Symposium on Intelligent Systems and Informatics (Sisy) (2014):221-225, conv_848 .